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Identifying the path choice of digital economy to crack the “resource curse" in China from the perspective of configuration

Author

Listed:
  • Feng, Yanchao
  • Gao, Yue
  • Xia, Xiqiang
  • Shi, Ke
  • Zhang, Ci
  • Yang, Le
  • Yang, Liwei
  • Cifuentes-Faura, Javier

Abstract

Against the backdrop of the “green economy", economic growth and environmental protection are perceived as interdependent and inseparable entities. The digital economy, as a novel economic paradigm, plays a crucial role in unraveling the “resource curse" of excessive resource consumption under traditional development models. This study employs the fuzzy set qualitative comparative analysis (fsQCA) method investigate the configuration effects of technical, organizational, and environmental factors on addressing the “resource curse" across 30 provinces (autonomous regions, municipalities) in China. It also examines the interactive matching relationships among different factors and the heterogeneity of the digital economy in mitigating the “resource curse". It is significantly established that breaking the “resource curse" does not have a single necessary condition, and the environmental factors emerge as pivotal elements for each province in this process. Considering the role of digital economy, there are four distinct configuration paths for the digital economy to mitigate the “resource curse", each exhibiting significant regional and industrial dependence heterogeneity. This research approach integrates the digital economy with traditional resource economies, aiming to explore new development patterns and theoretical frameworks. It also seeks to provide policymakers with practical strategies to guide economic and social transition towards a modernized path characterized by green, circular, and efficient development with the aid of the digital tools.

Suggested Citation

  • Feng, Yanchao & Gao, Yue & Xia, Xiqiang & Shi, Ke & Zhang, Ci & Yang, Le & Yang, Liwei & Cifuentes-Faura, Javier, 2024. "Identifying the path choice of digital economy to crack the “resource curse" in China from the perspective of configuration," Resources Policy, Elsevier, vol. 91(C).
    • Handle: RePEc:eee:jrpoli:v:91:y:2024:i:c:s0301420724002794
    DOI: 10.1016/j.resourpol.2024.104912
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    References listed on IDEAS

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    1. Midttun, Alte & Piccini, Proadpran Boonprasurd, 2017. "Facing the climate and digital challenge: European energy industry from boom to crisis and transformation," Energy Policy, Elsevier, vol. 108(C), pages 330-343.
    2. Marek Szturo & Bogdan Włodarczyk & Alberto Burchi & Ireneusz Miciuła & Karolina Szturo, 2021. "Improving Relations between a State and a Business Enterprise in the Context of Counteracting Adverse Effects of the Resource Curse," Sustainability, MDPI, vol. 13(3), pages 1-14, January.
    3. Jan Mendling & Brian T. Pentland & Jan Recker, 2020. "Building a complementary agenda for business process management and digital innovation," European Journal of Information Systems, Taylor & Francis Journals, vol. 29(3), pages 208-219, May.
    4. Thomas Greckhamer, 2016. "CEO compensation in relation to worker compensation across countries: The configurational impact of country-level institutions," Strategic Management Journal, Wiley Blackwell, vol. 37(4), pages 793-815, April.
    5. wael AL-khatib, Ayman, 2023. "Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework," Technology in Society, Elsevier, vol. 75(C).
    6. Chenhui Ding & Chao Liu & Chuiyong Zheng & Feng Li, 2021. "Digital Economy, Technological Innovation and High-Quality Economic Development: Based on Spatial Effect and Mediation Effect," Sustainability, MDPI, vol. 14(1), pages 1-21, December.
    7. Qian, Xiangyan & Wang, Di & Wang, Jia & Chen, Sai, 2021. "Resource curse, environmental regulation and transformation of coal-mining cities in China," Resources Policy, Elsevier, vol. 74(C).
    8. Chatterjee, Sheshadri & Rana, Nripendra P. & Dwivedi, Yogesh K. & Baabdullah, Abdullah M., 2021. "Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    Full references (including those not matched with items on IDEAS)

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